Lies, damned lies, and GTM statistics
Getting a 360 degree view of GTM Operations through cross-functional data analytics
- January 10, 2023
Lies, damned lies, and GTM statistics
Remember the blind men and the elephant. Looking at something from just one fixated view is dangerous and can produce misleading or incorrect insights.
Consider this situation. A GTM team generates several leads through a paid advertising campaign in a quarter compared to all other lead sources including SEO. Marketing managers show proof of MQLs (see campaign C below) and propose higher budgets for the same ad campaign in the future. What should you do?
What you have been presented is just one side of the story. A deeper end-to-end analysis indicates that lead conversion rates to revenue are better for several other lead sources than the suggested ad campaign. A separate look at spend data takes the analysis even further and shows that ARR/$ of spend is actually amongst the lowest for the ad campaign. So rather than put more money into the campaign, it may make sense to instead pull back our spend on this activity.
In another example, a high ACV doesn’t necessarily mean that the organization is good at enterprise sales. Perhaps the issue is that the team is not generating enough leads in mid-market or small business where the conversion rate is much higher. In other words, the high ACV may be misleadingly high, driven by GTM mistakes that are actually holding us back on actual business growth.
Making decisions based on GTM stats is a core activity for GTM leaders. However, as we have just seen, these insights can be a double-edged sword, especially when you look at them in silos.
The Role of RevOps In Silo Busting
Revenue Operations is a function specifically created to remove domain-specific siloes and biases. On the one hand, when creating a revenue operations team, especially by bringing together previously-siloed teams, it is important to set up the team in an agenda-neutral manner with a common set of cross-functional KPIs to ensure that they do not bring long-running biases with them. At the same time, as a RevOps leader, it’s paramount to reconcile Go-to-market (GTM) insights across all sources. Making decisions by looking at insights from just one source can yield half-truths and lead to incorrect conclusions.
In order to get a holistic 360-degree view of all GTM, revenue teams need to analyze data from multiple data sources across marketing, sales, and customer success – CRM, marketing automation platforms, website analytics, support systems, etc.
Correlating insights across multiple data sources
There are several ways to try and correlate these cross-functional insights. You can use IT analysts to pull reports together using business intelligence tools like Tableau or Power BI. Or, you can create a data lake to aggregate data from diverse sources into one place. The former approach is difficult to execute at the speed of business. Tight budgets mean that IT analyst teams are under-resourced and over-burdened, and the turnaround time for this analysis takes too long. The data lake approach is very expensive and beyond the reach of many organizations.
A 3rd approach is to apply a layer of intelligence over all of the cross-functional data. While allowing the individual tools to operate unchanged in their specialization, this RevOps insights layer can apply data transformation, analytics, and AI to develop a single source of truth for the entire organization to draw on. It can reconcile across the underlying data sources and component-specific insights to help revenue leaders gain a more rounded understanding of the state of RevOps for the organization.
BigLittle Can Help
BigLittle was founded to provide RevOps leaders with the tools, techniques and insights to help them transform functionally siloed marketing, sales and customer success ops teams into a fully-integrated revenue operations organization. Talk to us to learn how our cross-functional GTM insights can help you get a complete picture of what’s happening and make unbiased and informed decisions for your revenue teams.
